arXiv Machine Learning July 21, 2026 By Maneesha Perera, Julian De Hoog, Kasun Bandara, Hansani Weeratunge, Saman Halgamuge

Distributed solar generation forecasting using attention-based deep neural networks for cloud movement prediction

Read the original on arXiv Machine Learning →

arXiv:2411. 10921v2 Announce Type: replace Abstract: Accurate forecasts of distributed solar generation are necessary to maintain grid stability amid the increased uptake of distributed solar photovoltaic (PV) systems.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

computer-vision

arXiv Machine Learning

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FarSky: Task-Aware Latent-Space Coupling for Generative Intra-Hour Solar Forecasting

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arXiv Machine Learning

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Step-adaptive multimodal fusion network with multi-scale cloud feature learning for ultra-short-term solar irradiance forecasting

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By Jingxin Zhang Xiaoqin Wang

multimodal benchmarks

arXiv AI

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Self-Gating Attention for Efficient Time Series Forecasting

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llms efficiency benchmarks

arXiv Machine Learning

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An AI-Based Decision-Support Pipeline for Day-Ahead Photovoltaic Forecasting

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safety

arXiv AI

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Stable Attention Response for Reliable Precipitation Nowcasting

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By Penghui Wen, Zexin Hu, Sen Zhang, Patrick Filippi, Xiaogang Zhu, Allen Benter, Thomas Bishop, Zhiyong Wang, Kun Hu

diffusion multimodal benchmarks

arXiv Machine Learning

Jul 31

Meteosat Third Generation imagery improves CNN-based SSI retrieval

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By Gordei Prib\~otkin, Piia Post, Velle Toll

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